Heuristics that almost always work

The Hydroxychloroquine discussion is pretty bad as well.

We were confidently against Hydroxychloroquine because it was well tested in the RECOVERY trial in June 2020 [1].

The time to be optimistic was during the trial-phase of the test. Once that time passed, everything beyond that point was unnecessary and unhelpful hype.

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What's amazing to me, is that the RECOVERY trials showed that Dexamethasone cut the death rates in half [2]. Where did the Dexamethasone hype go? Why was the political discussion on the snake-oil Hydroxychloroquine?

Even months before we had a vaccine, doctors had discovered how to save roughly 10% of lives in the most severe category. (29.3% death rate vs. 41.4% death rate for those on ventilators). Doctors quickly started using the $20 steroid to save so many lived throughout the pandemic.

Instead of hyping the stuff that _WORKED_, the political system was hyping snake-oil like Hydroxychloroquine and Ivermectin. Why were so many people optimistic on such bullshit?

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Here is where being skeptical helps. Whenever Hydroxychloroquine or Ivermectin came up in a stupid discussion, I'd pivot the discussion towards Dexamethasone and Monoclonal antibodies. People need hope. People want hope. Before we had vaccines, people wanted to know that doctors had an idea of what to do. Dexamethasone and Monoclonal Antibodies did the job and did it properly (saving lives long before vaccines were developed). No one cared if it was "hydroxychloroquine" or "dexamethasone", these are all just giant chemical that few people memorize. People wanted hope, and it was important we kept that hope factually correct.

You can't promise the world with bullshit snake oil. When someone gets COVID19, they'll demand Ivermectin (yes, my sister is a doctor and she's seeing patients who are literally dying and demanding Ivermectin from her). Ivermectin has given these people false hope and is turning them away from the actual care that would save them.

[1]: https://www.recoverytrial.net/news/statement-from-the-chief-...

[2]https://www.nejm.org/doi/full/10.1056/nejmoa2021436

These heuristics seem be the same thing: The null hypothesis is the most likely.

Probably not. But they aren't affected by the previous N climbs, at least as described by GP post. They are considering a fixed odds event, and the probability of (bad thing happens) over a sample path through time. That's not the turkey fallacy.

In other words , the difference between the turkey and the climber is the climber knows the odds (at least nominally) , and it’s important .

PNG has a lot of eucalyptus trees, and some species drop their branches with zero warning, which originated as a mechanism for surviving droughts. I don't know enough to tell whether that's what's going on in the estimate.

Are there 100-year events associated with 100 square-inch plots of floor? No... But there are with coastlines, cities, dams, forests, deserts, islands, volcanoes, etc.

Of course there are other compounding factors. Not all events are one-in-one-hundred; some are one-in-ten, others are one-in-five-hundred, and with increasing scarcity by order of magnitude.

Another compounding factor is that the borders for "geographical areas" are fuzzy. Does a one-in-a-hundred year event that happens in Vermont also qualify as having happened in New Hampshire? Probably depends on the type and the specific measurements and the expectation according to history.

And what about aggregate events? E.g. "It's been five hundred years since we've seen this many tornadoes, which tend to happen once every ten years."

And in the opposite direction of the 100 square-inch plot of ground, there is blurring in the other direction: What do they mean in aggregate if they are fewer than expected at a global scale?

So my original comment was just a simple way of taking the average of all of these competing factors and stating a general truth that's somewhere in the middle. If you have X things that are expected to have 1/Y probabilities, then the probability of you experiencing any of them is not 1/Y, it's more like X/Y. (As in very likely.. that's more than 1 so obviously not mathematically correct.) But we often don't think about rare events this way - as no specific event being probable, but some collection of improbable events being almost certain. We perceive them all as 1/Y. It's just a very local way of thinking.